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Testing the semi-explicit assembly model of aqueous solvation in the SAMPL4 challenge

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Abstract

Here, we test a method, called semi-explicit assembly (SEA), that computes the solvation free energies of molecules in water in the SAMPL4 blind test challenge. SEA was developed with the intention of being as accurate as explicit-solvent models, but much faster to compute. It is accurate because it uses pre-simulations of simple spheres in explicit solvent to obtain structural and thermodynamic quantities, and it is fast because it parses solute free energies into regionally additive quantities. SAMPL4 provided us the opportunity to make new tests of SEA. Our tests here lead us to the following conclusions: (1) The newest version, called Field-SEA, which gives improved predictions for highly charged ions, is shown here to perform as well as the earlier versions (dipolar and quadrupolar SEA) on this broad blind SAMPL4 test set. (2) We find that both the past and present SEA models give solvation free energies that are as accurate as TIP3P. (3) Using a new approach for force field parameter optimization, we developed improved hydroxyl parameters that ensure consistency with neat-solvent dielectric constants, and found that they led to improved solvation free energies for hydroxyl-containing compounds in SAMPL4. We also learned that these hydroxyl parameters are not just fixing solvent exposed oxygens in a general sense, and therefore do not improve predictions for carbonyl or carboxylic-acid groups. Other such functional groups will need their own independent optimizations for potential improvements. Overall, these tests in SAMPL4 indicate that SEA is an accurate, general and fast new approach to computing solvation free energies.

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Acknowledgments

The authors thank Karisa L. Wymer (UC Irvine) and David L. Mobley (UC Irvine) for helpful discussions. The authors appreciate the support from National Institutes of Health Grant GM063592.

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Authors and Affiliations

  1. Departments of Chemistry and Physics, Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, 11794, USA

    Libo Li & Ken A. Dill

  2. Department of Chemistry, Oklahoma State University, Stillwater, OK, 74078, USA

    Christopher J. Fennell

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  1. Libo Li
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  2. Ken A. Dill
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  3. Christopher J. Fennell
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Correspondence to Christopher J. Fennell.

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Li, L., Dill, K.A. & Fennell, C.J. Testing the semi-explicit assembly model of aqueous solvation in the SAMPL4 challenge. J Comput Aided Mol Des 28, 259–264 (2014). https://doi.org/10.1007/s10822-014-9712-8

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  • DOI: https://doi.org/10.1007/s10822-014-9712-8

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